remove api backward compatibility and deprecation tests

Author: drbenvincent

causalpy/pymc_experiments.py

@@ -725,122 +725,3 @@ def test_inverse_prop():
     assert all(isinstance(ax, plt.Axes) for ax in axs)
     with pytest.raises(NotImplementedError):
         result.get_plot_data()
-
-
-# DEPRECATION WARNING TESTS ============================================================
-
-
-def test_did_deprecation_warning():
-    """Test that the old DifferenceInDifferences class raises a deprecation warning."""
-
-    with pytest.warns(DeprecationWarning):
-        df = cp.load_data("did")
-        result = cp.pymc_experiments.DifferenceInDifferences(
-            df,
-            formula="y ~ 1 + group*post_treatment",
-            time_variable_name="t",
-            group_variable_name="group",
-            model=cp.pymc_models.LinearRegression(sample_kwargs=sample_kwargs),
-        )
-        assert isinstance(result, cp.DifferenceInDifferences)
-
-
-def test_rd_deprecation_warning():
-    """Test that the old RegressionDiscontinuity class raises a deprecation warning."""
-
-    with pytest.warns(DeprecationWarning):
-        df = cp.load_data("rd")
-        result = cp.pymc_experiments.RegressionDiscontinuity(
-            df,
-            formula="y ~ 1 + bs(x, df=6) + treated",
-            model=cp.pymc_models.LinearRegression(sample_kwargs=sample_kwargs),
-            treatment_threshold=0.5,
-            epsilon=0.001,
-        )
-        assert isinstance(result, cp.RegressionDiscontinuity)
-
-
-def test_rk_deprecation_warning():
-    """Test that the old RegressionKink class raises a deprecation warning."""
-
-    with pytest.warns(DeprecationWarning):
-        kink = 0.5
-        df = setup_regression_kink_data(kink)
-        result = cp.pymc_experiments.RegressionKink(
-            df,
-            formula=f"y ~ 1 + x + I((x-{kink})*treated)",
-            model=cp.pymc_models.LinearRegression(sample_kwargs=sample_kwargs),
-            kink_point=kink,
-        )
-        assert isinstance(result, cp.RegressionKink)
-
-
-def test_its_deprecation_warning():
-    """Test that the old InterruptedTimeSeries class raises a deprecation warning."""
-
-    with pytest.warns(DeprecationWarning):
-        df = (
-            cp.load_data("its")
-            .assign(date=lambda x: pd.to_datetime(x["date"]))
-            .set_index("date")
-        )
-        treatment_time = pd.to_datetime("2017-01-01")
-        result = cp.pymc_experiments.InterruptedTimeSeries(
-            df,
-            treatment_time,
-            formula="y ~ 1 + t + C(month)",
-            model=cp.pymc_models.LinearRegression(sample_kwargs=sample_kwargs),
-        )
-        assert isinstance(result, cp.InterruptedTimeSeries)
-
-
-def test_sc_deprecation_warning():
-    """Test that the old SyntheticControl class raises a deprecation warning."""
-
-    with pytest.warns(DeprecationWarning):
-        df = cp.load_data("sc")
-        treatment_time = 70
-        result = cp.pymc_experiments.SyntheticControl(
-            df,
-            treatment_time,
-            control_units=["a", "b", "c", "d", "e", "f", "g"],
-            treated_units=["actual"],
-            model=cp.pymc_models.WeightedSumFitter(sample_kwargs=sample_kwargs),
-        )
-        assert isinstance(result, cp.SyntheticControl)
-
-
-def test_ancova_deprecation_warning():
-    """Test that the old PrePostNEGD class raises a deprecation warning."""
-
-    with pytest.warns(DeprecationWarning):
-        df = cp.load_data("anova1")
-        result = cp.pymc_experiments.PrePostNEGD(
-            df,
-            formula="post ~ 1 + C(group) + pre",
-            group_variable_name="group",
-            pretreatment_variable_name="pre",
-            model=cp.pymc_models.LinearRegression(sample_kwargs=sample_kwargs),
-        )
-        assert isinstance(result, cp.PrePostNEGD)
-
-
-def test_iv_deprecation_warning():
-    """Test that the old InstrumentalVariable class raises a deprecation warning."""
-
-    with pytest.warns(DeprecationWarning):
-        df = cp.load_data("risk")
-        instruments_formula = "risk  ~ 1 + logmort0"
-        formula = "loggdp ~  1 + risk"
-        instruments_data = df[["risk", "logmort0"]]
-        data = df[["loggdp", "risk"]]
-        result = cp.pymc_experiments.InstrumentalVariable(
-            instruments_data=instruments_data,
-            data=data,
-            instruments_formula=instruments_formula,
-            formula=formula,
-            model=cp.pymc_models.InstrumentalVariableRegression(
-                sample_kwargs=sample_kwargs
-            ),
-        )
-        assert isinstance(result, cp.InstrumentalVariable)